There are various pressures to develop new approaches to
the ecological risk assessment of chemicals. On the one hand there is pressure
to test more chemicals, leading to economic pressures to reduce the costs of
tests and to speed them up, and also ethical pressures to reduce the use of
animals in testing. One response to these pressures is to make better use of
observations on suborganismal responses arising from chemical perturbations to
make an assessment of the likelihood of impact on targets of concern.
Frameworks such as Adverse Outcome Pathway (AOP) take this approach. This
framework offers the promise of identifying mechanisms that are responsive to
chemical perturbation and of building in vitro testing methods around them. On
the other hand, there are also calls for developing more holistic risk
assessments that are more in tune with the needs of risk management, that
relate more obviously to the objects of protection, and that thus express
impacts in terms of health and/or ecosystem services. Finally, there are calls
for approaches that make more explicit links between exposure and effects and
that move away from expressing risks in terms of simple thresholds and toward
outputs that can better inform management decisions. Mechanistic effect models
encompass a broad range of quantitative tools to address these issues and
support the quantification of risks for tested and untested chemical stressors.

Speakers representing the academia, regulatory agencies,
and industry tripartite are participating in a workshop intended to discuss how
lessons learned from recent and ongoing initiatives in Europe and North America
could facilitate the development and implementation of predictive modeling
tools in the regulatory risk assessment of chemicals. The workshop is a mix of
invited talks and panel discussions where audience participation will be
encouraged.

Getting at What Really Matters in Managing Ecological
Risks Through Mechanistic Effect Models

Ecological risk assessments ought to be expressed in terms
of the way ecological things that matter to the public are affected by
exposure to a chemical. They rarely are. There is a big gap between these
protection goals and the endpoints that we measure and use in assessments.
This means that judgments (involving values) on what the assessments mean for
management are often made by assessors and managers. Mechanistic effect
models, in association with ecosystem service thinking, have the potential
for making the links between test endpoints and what managers need to manage
more explicit and (hopefully) more transparent.

CREAM is a Marie Curie Initial Training Network funded by
the EC, which involves 23 partners from academia, regulatory authorities and industry.
It aimed at training 23 PhD/post-docs over Europe in ecological modeling and
risk assessment. It allowed developing mechanistic effect models (MEMs) for a
suite of species/systems relevant for the risk assessment of plant protection
products (PPP) in Europe. The emphasis was put on exploring links between
exposure and effects and forecasting population-level effects, so as to meet
protection goals defined by the recent EU regulation, and on developing
guidance for good modelling practice. Models were experimentally validated
and documented using the TRACE framework. Overall, CREAM has provided models,
guidance on good modelling practices and trained modelers/stakeholders, which
will contribute to MEM implementation in future risk assessments of PPP in
Europe.

How to use effects models in pesticide risk assessment –
recommendations of the MODELINK workshop

Mechanistic effect models offer several possibilities to
improve our environmental risk assessments but until now they have not often been
accepted in the regulatory risk assessment of plant protection products in
Europe. However, now some initiatives and projects address the different
challenges to improve the situation. The SETAC Europe workshop MODELINK
focused on when and how to use such models within our risk assessment
schemes. Six case studies cover the different groups of non- target organisms
which are routinely considered in the environmental risk assessment of
pesticides and models were used to extrapolate e.g. from the constant
exposure situation in the laboratory to variable exposure in space and time
in the field or
from measured
individual level
endpoints to effects
on populations. Examples of problem definitions, species and scenario
selection, and model outputs will be shown. The models provided more detailed
and more realistic outputs compared to the tiered experimental approach
alone. However, for using these outputs for risk management more explicit
decisions on acceptable effects have to be made. One of the main MODELINK
recommendations is to define specific quantitative protection goals for the
different potentially affected key drivers of the ecosystem services we want
to protect in agricultural landscapes.

Ecological risk methods and tools
are necessarily diverse to account for different combinations of receptors,
exposure processes, effects estimation, and degree of conservatism/realism
necessary to support chemical-based assessments. These tools have been continuously
developed since the early 1980s and are currently accessible through a number
of software platforms (e.g., DOS-based FORTAN executables, spreadsheet-based
calculations, form-based Windows programs) that can lead to inefficiencies
and inconsistencies when used together to inform an assessment. Recent
advances in cloud-based computing provides an opportunity to integrate
commonly used ecological risk models as a web application dashboard that
allows for the modular execution of individual models as well as the
simultaneous execution of multiple models in a serial or parallel manner.
We have created an integrated web-based
tool, the übertool (http://www.ubertool.org), designed to run EPA models that
estimate exposure doses and ecological risks under the Federal Insecticide,
Fungicide, and Rodenticide Act (FIFRA) and the Endangered Species Act (ESA).
These models include a number of aquatic, terrestrial, and atmospheric
deposition fate and transport models used to estimate pesticide exposures and
effects for a range of ecological receptors. We have also extended the
übertool's web-based framework to create the untertool
(http://untertool.appspot.com), which gives examples of population dynamic
models that are often used for educational and research purposes. By
aggregating such models into a virtual dashboard and providing them as web
services, we hope to help narrow the gap between ecological hazard
assessment/risk quotient approaches that address individual effects endpoints
and the difficult task of reliably assessing ecological endpoints at the
population level. Closing this gap is necessary to create a common,
scientifically credible approach to resolve such endpoint assessment
discrepancies and is a current focus of interagency discussion in the US with
respect to ecological risk activities in support of the Endangered Species
Act.

Evaluating the Protectiveness of Water Quality Criteria
for Threatened or Resilient Species: Judgments, Models, and Back to Judgments

Water quality criteria are often derived with at least an
implicit goal of protecting populations, communities, and ecosystems. This is
usually done by extrapolating laboratory toxicity data to populations in the
wild through informal assumptions and judgments. Population modeling can be
useful exercises for extrapolating laboratory effects data to populations,
sensitivity analyses, and contrasting management alternatives. However, the
construction of population models requires many decisions, some of which in
turn must be based on assumptions and judgments. Finally, the modeling
results must be interpreted and presented to managers, which requires
additional judgments by the analysts how to portray the results. These ideas
will be illustrated through examples with a threatened anadromous Chinook
Salmon population and with a resilient, "weedy” invertebrate, the amphipod
Hyalella sp.

Recommendations for Ecological Models to Assess Risks to
Endangered and Threatened Species

Species in danger of local or global extinction typically
are granted a special status and a higher level of protection from the
adverse consequences of exposure to toxic chemicals and/or pesticides. Recent
legal challenges in the United States have questioned the methods used to
assess risks of existing or new pesticides to such species, highlighting the
differences between the chemocentric approach used by the U.S. Environmental
Protection Agency when registering pesticides, and the biocentric approach
use by the U.S. Fish and Wildlife Service or the National Oceanic and
Atmospheric Administration when writing their biological opinions. The
National Academy of Sciences (NAS) convened a special committee to identify
commonalities between the approaches and recommend a unified method for
assessing risks to listed species. The NAS committee ultimately recommended a
tiered approach that looks first at exposure and use patterns to determine
species potentially at risk, then applies screening tools to assess the
relationship between the toxicological mechanisms of action and the
physiology of the species of concern. Those chemicals that result in a
conclusion of "likely to affect” a listed species' survival or reproduction
are further evaluated at the highest tier, where population models and
environmental monitoring are employed to estimate whether, and by how much,
the trend towards extinction would be exacerbated by chemical exposure. To
account for uncertainty in both effects and exposure assessments, a
probabilistic approach is preferred. The recommended tiered approach
highlights the need for the integration of toxicological and ecological
methods when addressing questions of populations and extinction rates.

Linking exposure and effects in ERA – lessons learned from
a nanoparticle example

In environmental risk assessment (ERA) of chemicals the
procedures for assessing exposure and effects are largely uncoupled, and the
methods accepted and used in the two aspects of ERA are immensely different.
For exposure assessment it is widely accepted to use models of differing
complexity based on certain release- and environmental scenarios. On the
other hand, effect assessments are largely based on results from simplified
laboratory experiments, that rarely include environmental variability and
which are analyzed by simple static models such as dose-response models or
species sensitivity distribution models. More recently the use of mechanistic
effects models (MEMs) in ERA of, in particular, pesticides has been promoted
and is gaining momentum. So far attempts to explore the use of MEMs in ERA of
other types of chemicals are more limited. In this talk I will present to you
some of the lessons learned from an EU financed project on Modeling
Nanoparticle Toxicity (ModNanoTox) related to the potential implementation
and use of MEMs in nanoparticle ERA. The aim of the presentation is twofold:
1) to show that MEMs offer an ecologically more relevant way of addressing
effects of chemicals in the environment, both with regard to including the
appropriate protection goal and the relevant environmental compartment, and
2) to show that such models may also provide an opportunity to directly link
exposure and effect assessments.

Mechanistic Models to Explore Population Impacts of Spatially
Variable Exposure

In assessing ecological risks for terrestrial ecosystems,
heterogeneous distribution of contaminants is often disregarded. We developed
a spatially explicit individual-based model to explore how the interaction of
different patterns of microscale fragmentation caused by the presence of a
persistent pollutant heterogeneously distributed in soil, combined with
disturbance events, which can be both natural (e.g. drought) and
anthropogenic (e.g. pesticide applications) stress factors, affects the
population dynamics of the collembolan, F. candida, and its recovery after
stress. Individuals in the model can sense and avoid contaminated habitat.
Avoidance of toxicant influences the feeding behavior of the organisms, and
this in turn affects all the other biological processes. Simulation results
show that when the uncontaminated area is small (< 10%), stable population
size is bigger in the case of spatially correlated distributions of toxicant,
whereas as the proportion of clean habitat increases, population growth is
higher with uncorrelated contamination. This pattern changes when avoidance
behavior is excluded from the model, as does population recovery after a
series of disturbance events. The model suggests that a combination of
heterogeneous contamination and multiple stressors can lead to unexpected
effects of toxicants at the population level. Individual-based models can
help to understand these effects and can add ecological realism to
environmental risk assessment of chemicals.

This presentation will provide an
overview of the models currently used by the office of United States Environmental
Protection Agency's Office of Pesticide Programs for assessing the
environmental fate and associated ecological risks of pesticides. Models that
are currently in development, including probabilistic approaches for
assessing effects to birds and honey bee colony simulation models will also
be discussed.

An adverse outcome pathway (AOP) is a conceptual framework
linking molecular-level initiating event(s) with adverse effects at the
individual and population level.
Future environmental risk assessments are anticipated to rely heavily
on QSAR and in vitro derived toxicity data, which will need to be
extrapolated across biological scales to relevant risk assessment
endpoints.
To provide a stronger
mechanistic basis for extrapolation, computational models are being developed
that more closely link toxicant induced cellular or sub-cellular
perturbations with traditional apical or whole organism measures of
response.
An additional component of
the AOP is to incorporate environmental fate and toxicokinetic models to
convert in vitro exposure levels into the corresponding environmental levels
needed to achieve relevant target organ concentrations (sometimes referred to
as reverse toxicokinetics).
In this
presentation, I will provide a description of the AOP process with examples
of approaches being used for in vitro extrapolation and reverse
toxicokinetics including recent developments in computational models for
aquatic species.

Important progress has been made
in the development, communication, and testing of mechanistic effect models
for ecological risk assessment. Much of this progress has come out of
European initiatives, and most efforts have been focused on using models to
assess the risks of pesticides in agricultural landscapes under European
legislation. Given these advances, it is now time to consider whether and how
such models have a role to play in the risk assessment of other classes of
chemicals, to systematically assess the opportunities and challenges for
using models in different regulatory contexts, such as under REACH or for
Superfund assessments, and to expand the models' capabilities to cross more
levels of biological organization. A key question is whether it is possible
to develop a single, integrated modeling framework that would allow robust
linkages to be made from molecular events, through organismal responses, to
population- and community-level impacts and ultimately to the delivery of
ecosystem services that are the targets of protection. Advances in the
computational sciences and in sensor technology offer promising tools, but
success will require multi-disciplinary collaboration and active engagement
of all stakeholder groups.

BACKGROUND INFORMATION

Background – Activities

During the last decade a series of international
workshops, hosted in both Europe and North America, have explored the
opportunities and obstacles for implementing ecological modeling into
regulatory risk assessment. They include the Pellston Workshop on
Population-Level Ecological Risk Assessment held in Roskilde, Denmark in 2003;
the LEMTOX Workshop, held in Leipzig, Germany in 2007, the USEPA Risk Assessment
Forum Technical Workshop on Population-Level Ecological Risk Assessment held in
Washington, DC in 2008, and the Roskilde Workshop on Integrating Population
Modeling into Ecological Risk Assessment (RUC09), held in Roskilde, Denmark in
2009.

Chemical Risk Effects Assessment Models (CREAM) is a
"Marie Curie Initial Training Network (ITN)” funded by the European Commission
within the 7th Framework Programme, from 2009-2013.
Its focus has been on developing Good Modeling
Practice and on first-class training of early stage researchers. CREAM is very
likely the largest joint project worldwide developing mechanistic effect models
for risk assessment of chemicals.

A SETAC Advisory Group on Mechanistic Effect Models for
Ecological Risk Assessment of Chemicals (MeMoRisk) was established in 2008. The
overall aim of the advisory group is to explore and evaluate the benefit of
mechanistic effect modeling for the risk assessment of chemicals.

A two-part SETAC Europe technical workshop, MODELINK, was
held in the fall of 2012 (Le Croisic, France) and spring 2013 (Monschau,
Germany) to provide guidance for when and how to apply ecological models to
regulatory risk assessment of pesticides by developing specific case studies
representing common risk scenarios.